Test Organizations

Test Organizations
TestOrgNumber EIN Name State MajorGroup NTEE.CC TotalExpense CEOCompensation
1 237392118 THE LEARNING CENTER AT PIPER’S HILL CT 2 B20 2221843 92539.91
2 350868101 HUNTINGTON UNIVERSITY IN 11 B43 42079670 408004.44
3 208969896 BROWN COUNTY ORAL HEALTH PARTNERSHIP WI 4 E99 3744664 116212.53
4 160743979 NICHOLAS H NOYES MEMORIAL HOSPITAL NY 12 E22 59517721 223204.75
5 260317963 REDLINE CO 1 A40 1752816 118630.15
6 943019570 THE PROTEIN SOCIETY CA 7 U03 1200932 173402.65
7 205935069 QUIT DOC RESEARCH AND EDUCATION FL 2 B05 1661923 89324.41

Weight Sets

Weight Set 1

level geo r.mission s.mission
1 1 1 1
2 1 1 1
3 1 1 1
4 1 1
5 1

Weight Set 2

level geo r.mission s.mission
1 2 3 3.0
2 2 2 2.0
3 1 1 1.0
4 1 1.0
5 0.5

Weight Set 3

level geo r.mission s.mission
1 5 5 5.0
2 2 2 2.0
3 1 1 1.0
4 1 1.0
5 0.5

Basic Comparison Plots

X facet (columns) is weight set number, Y facet (rows) is test org number.

Correlation Plots

directories <- paste0(current.dir)

plots <- list.files(directories, pattern="*.jpg")
plots <- paste0( directories, "/", plots)

index <- 1

if(length(plots > 0)){
  p <-paste0('<table border="1">')
# #create an html table with float left/right, whatever....
  for(i in seq(1,length(plots),nrow(weights))){
    p <- paste0(p, '<tr>')
    
    for(j in 1:nrow(weights) ){
      p <- paste0(p, '<td height="450"><img src="',plots[i+j-1],'" height="400" width="400"/></td>')
    }
    p <- paste0(p, '</tr>')
    
    
    }
p <- paste0(p, '</table>')
}

cat(p)

Proxy Subway plot


Test Set 1
[1] “Correlations for Test Org 1”

First Weight Set Second Weight Set corr(Distance) cor(Rank)
1 2 0.95316 0.98204
1 3 0.87942 0.95203
2 3 0.97260 0.98925


Test Set 2
[1] “Correlations for Test Org 2”

First Weight Set Second Weight Set corr(Distance) cor(Rank)
1 2 0.97899 0.97575
1 3 0.93634 0.92749
2 3 0.97118 0.98406


Test Set 3
[1] “Correlations for Test Org 3”

First Weight Set Second Weight Set corr(Distance) cor(Rank)
1 2 0.96377 0.98445
1 3 0.89123 0.96007
2 3 0.96994 0.98847


Test Set 4
[1] “Correlations for Test Org 4”

First Weight Set Second Weight Set corr(Distance) cor(Rank)
1 2 0.95099 0.98254
1 3 0.85997 0.94553
2 3 0.96556 0.98613


Test Set 5
[1] “Correlations for Test Org 5”

First Weight Set Second Weight Set corr(Distance) cor(Rank)
1 2 0.96109 0.98614
1 3 0.88084 0.95965
2 3 0.96729 0.99055


Test Set 6
[1] “Correlations for Test Org 6”

First Weight Set Second Weight Set corr(Distance) cor(Rank)
1 2 0.96166 0.98932
1 3 0.89126 0.97245
2 3 0.97174 0.99434


Test Set 7
[1] “Correlations for Test Org 7”

First Weight Set Second Weight Set corr(Distance) cor(Rank)
1 2 0.95031 0.97570
1 3 0.87377 0.92252
2 3 0.96077 0.98211